Demand estimation apparatus

ABSTRACT

A demand estimation apparatus wherein one cycle of a demand fluctuating substantially cyclically is divided into a plurality of sections having predetermined time widths, the demand is measured by cumulating demand measurements taken a varying number of times for each section and assigning an increasing weighting parameter for successively newer measured values, an estimated demand for each section is calculated based on the measured values for the section and a weight coefficient, and the weight coefficient is changed in accordance with the number of times of cumulation of demand measurements.

BACKGROUND OF THE INVENTION

This invention relates to improvements in an apparatus for estimating ademand such as a traffic volume or an electric power load.

The traffic volume of elevators in a building, the electric power loadof a power station, or the like (hereinbelow, simply termed "demand")fluctuates irregularly when closely observed within a period of one day,but presents similar aspects for the same time zones when observed overseveral days. In, for example, an office building, elevator passengerson their way to their office floors crowd on the first floor during ashort period of time in the time zone in which they attend offices inthe morning. In the first half of the lunch hour, many passengers gofrom the office floors to a restaurant floor, while in the latter halfthereof, many passengers go from the restaurant floor to the officefloors. In addition, many passengers go from the office floors to thefirst floor in the time zone in which they leave the offices in theevening. The volumes of traffic in the up direction and in the downdirection are nearly equal in the daytime time zones other thanmentioned above, while the volume of traffic becomes very smallthroughout the nighttime.

In order to deal with the traffic in the building changing in thismanner by means of a limited number of elevators, the elevators areusually operated under group supervision. When a hall call is registeredanew, it is tentatively assigned to respective elevators, and thewaiting times of all hall calls, the possibility of the full capacity ofpassengers, etc., are predicted so as to select from among the elevatorsthe optimum one to respond to the new hall call. In order to executesuch predictive calculations, traffic data peculiar to each building isrequired. For example, data on the number of passengers who get on andoff the cage of each elevator at intermediate floors is required forpredicting the possibility of full capacity. When such traffic datawhich changes every moment is stored each time, an enormous memorycapacity is necessitated, which is not practical. Usually, the requiredmemory size is reduced by dividing the operating period of time in oneday into several time zones and storing only the average traffic volumesof the respective time zones. After the completion of the building,however, there is a possibility that traffic data will change inaccordance with changes in personnel organization in the building, andhence, it is difficult to obtain good traffic data with which the demandcan be predicted accurately. For this reason, a system has beendeveloped, for example as disclosed in copending application Ser. No.473,359 filed Mar. 8, 1983 now U.S. Pat. No. 4,567,566 and U.S. Pat. No.4,524,418 wherein traffic conditions in the building are detected so asto sequentially improve the traffic data.

More specifically, the operating period of time in one day is dividedinto K time zones (hereinbelow, termed "sections"), and a time(hereinbelow, termed "boundary") by which a section k-1 and a section kare bounded is denoted by t_(k) (k=2, 3, . . ., K). Times t_(l) andt_(k+l) are the starting time and end time of the elevator operation,respectively. The average traffic volume P_(k) (l) of the section k onthe l-th day is given by the following Equation (1): ##EQU1##

Here, X_(k) ^(u) (l) is a column vector of F-1 dimensions (where Fdenotes the number of floors) the elements of which are the number ofpassengers to get on cages in the up direction at respective floors inthe time zone k of the l-th day. Similarly, X_(k) ^(d) (l), Y_(k) ^(u)(l) and Yhd k^(k) (l) are column vectors which indicate the number ofpassengers to get on the cages in the down direction, the number ofpassengers to get off the cages in the up direction and the number ofpassengers to get off the cages in the down direction, respectively. Theaverage traffic volume (hereinbelow, termed "average demend") P_(k) (l)is measured by a passenger-number detector which utilizes load changesduring the stoppage of the cages of the elevators and/or industrialtelevision, ultrasonic wave, or the like.

First, the case where the representative value of the average demandP_(k) (l) of each time zone is sequencially corrected in a case wherethe boundary t_(k) is fixed is considered.

It is thought that the columns {P_(k) (1), P_(k) (2), . . .}of theaverage demands occurring daily will disperse in the vicinity of acertain representative value P_(k). Since the magnitude of therepresentative value P_(k) is unknown, it needs to be estimated by anymethod. In this case, there is the possibility that the magnitude of therepresentative value P_(k) will change. The representative value istherefore predicted by taking a linear weighted average given inEquations (2) and (3) below, whereby more importance is attached to theaverage demand P_(k) (l) measured latest, than to the other averagedemands P_(k)( 1), P_(k) (2), . . . and P_(k) (l-1). ##EQU2##

Here, P_(k) (l) is the representative value which has been predictedfrom the average demands P_(k) (l), ..., and P_(k) (l) measured till thel-th day, and P_(k) (O) is an initial value which is set at a suitablevalue in advance. λ_(i) denotes the weight of the average demand P_(k)(i) measured on the i-th day, and this weight changes depending upon aparameter a. More specifically, an increase in the value of theparameter a results in an estimation in which more importance isattached to the latest measured average demand P_(k) (l) than to theother average demands P_(k) (1), ... and Pk(l-1), and in which thepredictive representative value P_(k) (l) quickly follows up the changeof the representative value P_(k) . However, when the value of theparameter a is too large, it is feared that the predictiverepresentative value will change too violently in a manner to beinfluenced by the random variation of daily data. Meanwhile, Equations(2) and (3) can be rewritten as follows:

    P.sub.k (l)=(1-a)P.sub.k (l-1)+a P.sub.k (l)               (4)

    P.sub.k (O)=P.sub.k (O)                                    (5)

In accordance with the above Equation (4), there is the advantage thatthe weighted average of Equation (2) can be calculated without storingthe observation values P_(k) (i)(i=1, 2, ..., l-1) of the averagedemands in the past.

However, even in case of a demand which fluctuates cyclically, when thedemand is observed over a long term, the representative value P_(k)thereof might change greatly without remaining constant. By way ofexample, the traffic volume of elevators in a building is small at firstafter the completion of the building because there are comparatively fewresidents. The traffic volume increases little by little with the lapseof time, but some period is taken before the traffic volume becomesstable. In addition, in case of a building for rent, even when aconsiderable period of time has lapsed after the completion of thebuilding, the residents sometimes change suddenly. Also in this case,the representative value P_(k) of the demand changes.

In a case where, even when the magnitude itself of the representativevalue P_(k) of the demand has changed greatly as described above, thepredictive representative value P_(k) (l) of the representative valueP_(k) of the demand is calculated by the use of the parameter a which isset at a small value so as to avoid the influence of random variationsin daily data, and therefore cannot follow changes in the representativevalue P_(k) quickly and, therefore, greatly deviates from the actualdemand. In consequence, the calculations of the waiting time and thepossibility of full capacity being wrongly predicted arises, and theelevators are not group-supervised as intended. Conversely, when theparameter a is set at a large value so as to permit the predictiverepresentative value P_(k) (l) to quickly follow the representativevalue P_(k), the predictive representative value P_(k) (l) changesviolently due to the influence of random variation in daily data duringthe stable period of the representative value P_(k), so that similarinconveniences arise.

SUMMARY OF THE INVENTION

This invention improves the drawbacks described above, and has for itsobject to provide a demand estimation apparatus wherein among themeasurement values of a demand in each section, a new one is weightedmore than an old one, the new measurement value being then used, andonce a predetermined condition such as an increase in the number oftimes of cumulation of demand measurements has held, the degree of theweighting of the new measurement value is changed, whereby the demandcan be estimated at high precision.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 is a diagram of an up direction demand curve showing anembodiment in which a demand estimation apparatus according to thisinvention is applied to elevators;

FIG. 2 is a diagram of a down direction demand curve in the embodiment;

FIG. 3 is a block circuit diagram of the embodiment;

FIG. 4 is a diagram showing the content of a RAM in FIG. 3;

FIG. 5 is a diagram showing the content of a ROM in FIG. 3;

FIG. 6 is a diagram showing the general flow of programs;

FIG. 7 is a flow diagram of the operations of an initializing program inFIG. 6;

FIG. 8 is a flow diagram of the operations of a weight coefficientsetting program in FIG. 6;

FIG. 9 is a flow diagram of the operations of an up demand calculatingprogram in FIG. 6;

FIG. 10 is a flow diagram of the operations of an average demandestimating program in FIG. 6;

FIG. 11 is a diagram showing the content of the RAM in FIG. 3;

FIG. 12 is a diagram showing the content of the ROM in FIG. 3;

FIG. 13 is a flow diagram of the operations of the initializing programin FIG. 6;

FIG. 14 is a flow diagram of the operations of the weight coefficientsetting program in FIG. 6;

FIG. 15 is a flow diagram of the operations of the up demand calculatingprogram in FIG. 6; and

FIG. 16 is a flow diagram of the operations of the average demandestimating program in FIG. 6.

DESCRIPTION OF THE PREFERRED EMBODIMENT

Now, an embodiment of this invention will be described with reference toFIGS. 1-10.

In FIGS. 1 and 2, LDU indicates an up direction demand curve which isobtained in such a way that the numbers of persons who move in the updirection at predetermined times are measured and totaled for allfloors, whereupon the total value is cumulated every unit time DT (setat 5 minutes). Similarly, LDD indicates a down direction demand curvewhich corresponds to the down direction. T1 denotes the boundary whichis the starting time of a section I, T2 the boundary between the sectionI and a section II, T3 the boundary between the section II and a sectionIII, and T4 the boundary which is the end time of the section III. PU(1)and PD(1) designate an average up direction demand and an average downdirection demand in the section I, respectively. They correspond to theaverage traffic volume P_(k) (l) resulting when values obtained bycumulating the up direction demand LDU and the down direction demand LDDin the section I are respectively substituted into X_(k) ^(u) (l) andX_(k) ^(d) (l) in Equation (1), and Y_(k) ^(u) (l) =0 and Y_(k) ^(d) (l)=0 and are assumed. Likewise, PU(2) and PD(2) designate an average updirection demand and an average down direction demand in the section IIrespectively, while PU(3) and PD(3) designate an average up directiondemand and an average down direction demand in the section IIIrespectively.

In FIG. 3, numeral 1 indicates clock means for producing a timing signal1a each time a unit time DT lapses. Numeral 2 indicates a switch forappointing a weight coefficient, which is disposed on an operator'scontrol panel and which produces a signal 2a corresponding to any ofvalues 0-3 in accordance with respective positions of the switch 2.Shown at numeral 3 is a control device which basically comprises anelectronic computer such as a microcomputer, wherein symbol 3A denotesan input circuit which consists of a converter for receiving an input,symbol 3B a central processing unit (hereinbelow, termed "CPU"), symbol3C a random access memory (hereinbelow, termed "RAM") which stores datasuch as operated results, symbol 3D a read only memory (hereinbelow,termed "ROM") which stores programs and constant value data, and symbol3E an output circuit which consists of a converter for deliveringsignals from the CPU 3B. Numeral 4 indicates a group supervisory systemwhich group-supervises three elevator cages 5A-5C in accordance withsignals from the control device 3. Symbols 6A-6C denote well-knownnumber-of-persons detectors which are disposed on the cages 5A-5C toprovide signals proportional to the numbers of passengers, respectively.Symbols 7A-7C denote number-of getting on persons calculation device(for example, as disclosed in U.S. Pat. No. 4,044,860) which store theminimum values of input signals when doors are open, and subtract theminimum values from the values of the input signals when the doors areclosed, so as to calculate the numbers of persons who have gotten on thecages 6A-6C, respectively. Symbol 8A represents a change-over devicewhich produces a number-of-up passengers signal 8Aa during the asendingoperation of the elevator cage 5A, and a number-of-down passengerssignal 8Ab during the descending operation thereof. Likewise, symbols 8Band 8C represent change-over devices which produce number-of-uppassengers signals 8Ba and 8Ca and number-of-down passengers signals 8Bband 8Cb, respectively. A numbers-of-up passengers addition device 9A anda numbers-of-down passengers addition device 9B and respective inputsA-C and cumulate inputs D for the unit time DT so as to deliver thecumulative values as a number-of-up passengers signal 9Aa and anumber-of-down passengers signal 9Ba, respectively.

Reference is now had to FIGS. 4 and 5. Symbol TIME indicates a timeobtained from the timing signal 1a, signal 2a. Symbol LDU indicates anup direction demand corresponding to the number-of-up passengers signal9Aa, while symbol LDD a down direction demand corresponding to thenumber-of-down passengers signal 9Ba. Symbol SA designates a weightingparameter which corresponds to the parameter a in Equation (4), symbolCNT the number of times of cumulation by which the demand has beenmeasured, and symbol J a counter which is used as a variable indicativeof any of the sections I-III. Symbols PU(1)-PU(3) designate average updirection demands in the sections I-III respectively, while symbolsPD(1)-PD(3) similarly designate average down direction demands.PUL(1)-PUL(3) designate predictive average up direction demands whichcorrespond to representative values P_(k) (l) obtained by substitutingthe average up direction demands PU(1)-PU(3) into Equation (4),respectively, while symbols PDL(1)-PDL(3) similarly designate predictiveaverage down direction demands. Constant values N1, N2 and NMAX arerespectively set at 30, 60 and 120 (times), while constant valuesA(1)-A(3) are respectively set at 1/3, 1/6 and 1/9. Symbols T1-T4indicate boundaries which are respectively set at 87 (=7:15), 99(=8:15), 108 (=9:00) and 122 (=10:10). Symbols PU1-PU3 indicate theinitial values of the predictive average up direction demandsPUL(1)-PUL(3), which are respectively set at 65, 130 and 109(passengers/5 minutes), while symbols PD1-PD3 indicate the initialvalues of the predictive average down direction demands PDL(1)-PDL(3),which are respectively set at 5, 7 and 20 (passengers/5 minutes).

Reference is now had to FIGS. 6-10. Numeral 11 designates aninitializing program which sets the initial values of various data,numeral 12 an input program which accepts signals from the input circuit3A and sets them in the RAM 3C, numeral 13 a weight coefficient settingprogram which alters and corrects a weight coefficient and sets thecorrected weight coefficient, numeral 14 an up demand calculatingprogram which calculates the average up direction demands PU(1)-PU(3)measured in the respective sections I-III, numeral 15 a down demandcalculating program which similarly calculates the average downdirection demands PD(1) 14 PD(3), numeral 16 an average demandestimating program which calculates the predictive average up directiondemands PUL(1)-PUL(3) and predictive average down direction demandsPDL(1)-PDL(3) in the respective sections I-III, and numeral 17 an outputprogram which delivers the predictive average up direction demandsPUL(1)-PUL(3) and predictive average down direction demandsPDL(1)-PDL(3) from the output circuit 3E. Numerals 21 and 22 indicatethe operating steps of the initializing program 11, numerals 31-41 thoseof the weight coefficient setting program 13, numerals 51-58 those ofthe up demand calculating program 14, and numerals 61-65 those of theaverage demand estimating program 16.

The operations of this embodiment will now be described.

The number-of-persons detectors 6A-6C produce signals proportional tothe numbers of passengers in the cages 5A-5C, respectively. Thenumber-of-getting on person calculation devices 7A-7C calculate thenumbers of persons who have gotten on the cages 5A-5C, respectively.These numbers of persons are classified into the numbers of persons inthe up direction and in the down direction by the change-over devices8A-8C, whereupon the numbers of persons in the respective directions areadded by the number-of-up passengers addition device 9A and thenumber-of-down passengers addition device 9B. Thus, the number-of-uppassengers signal 9Aa and the number-of-down passengers signal 9Ba areprovided and sent to the input circuit 3A. In addition, the number ofcounts produced when the value "1" is counted every 5 minutes since atime 0 o'clock is provided as the timing signal 1a from the clock means1, and it is inputted to the input circuit 3A.

On the other hand, when the control device 3 is first connected to apower source, the initializing program 11 is actuated. Morespecifically, at Step 21, the initial values PU1-PU3 are respectivelyset for the predictive average up direction demands PUL(1)-PUL(3), andthe initial values PD1-PD3 are respectively set for the predictiveaverage down direction demands PDL(1)-PDL(3). Subsequently, when theinitial value "zero" is set for the number of times of cumulation CNT atStep 22, the control flow shifts to the input program 12.

The input program 12 is a well-known program which feeds the inputsignal from the input circuit 3A into the RAM 3C. By way of example,when the time is 8 o'clock, the input program reads the value 96 fromthe input circuit 3A and sets the time TIME of the RAM 3C at 96.Likewise, the switch signal 2a is received and set as the switch dataSWT, the number-of-up passengers signal 9Aa is received and set as theup direction demand LDU, and the number-of-down passengers signals 9Bais received and set as the down direction demand LDD.

Next, the weight coefficient setting program 13 is actuated. At Step 31,it is decided whether or not the first time zone in which the averagedemand is to be calculated has been reached. When the time TIME is equalto the boundary T1, the control flow proceeds to Step 32, whereat thenumber of times of cumulation CNT by which the demand has been measuredis increased by 1 (one). At Step 33, it is decided whether or not thenumber of times of cumulation CNT has become equal to or greater thanthe upper limit value NMAX (=120 times). When the number of times ofcumulation CNT is equal to or greater than the upper limit value, it isreset to zero at the next Step 34. Subsequently, what is appointed bythe weight coefficient appointing switch 2 is decided at Step 35. Whenthe switch data SWT is zero, it is indicated that the appointment by theswitch 2 is invalid. In this case, the weight coefficient SA conformingto the number of times of cumulation CNT is set by Steps 36-40. Morespecifically, when the number of times of cumulation CNT <the constantvalue N1 (=30 times) holds at Step 36, the weight coefficient SA is setat the constant value A(1) (=1/3) at Step 37. When the constant value N1(=30 times) ≦ the number of times of cumulation CNT <the constant valueN2 (=60 times) is decided at Steps 36 and 38, the weight coefficient SAis set at the constant value A(2) (=1/6) at Step 39. Further, when theconstant value N2 ≦ the number of times of cumulation CNT < the upperlimite value NMAX holds, the weight coefficient SA is set at theconstant value A(3) (=1/9) at Step 40. If the switch data SWT assumesany of values 1-3, it is expressed that the appointment by the switch 2has priority, and a constant value A(SWT) conforming to the value ofswitch data SWT is set as the weight coefficient SA at Step 41. When thetime TIME is unequal to the boundary T1 at Step 31, the above steps32-41 are not executed, and the weight coefficient SA is not corrected.

In this way, according to the weight coefficient setting program 13,before the average demand is calculated every day, the number of timesof cumulation CNT by which the demand has been measured is cumulated,and the weight coefficient is set by the appointment through the switch2 or in accordance with the number of times of cumulation CNT. Inaddition, when the number of times of cumulation CNT has become, atleast, equal to the upper limit value NMAX, it is reset to zero.

Next, the up demand calculating program 14 is actuated.

At Step 51, it is decided whether or not the time zone in which theaverage demand is to be calculated as been reached. When the time TIMEis smaller than the boundary T1, the control flow proceeds to Step 52,at which all the average up direction demands PU(1)-PU(3) are set atzero as the initializing operation for the calculation of the averagedemand. When the time TIME becomes equal to or greater than the boundaryT1 at Step 51, the control flow proceeds to Step 53. When the time TIMEis smaller than the boundary T2 here, the control flow proceeds to Step54, at which the average up direction demand PU(1) of the section I iscorrected by the use of the up direction demand LDU measured anew, so asto increase to the amount of the up direction demand per unit time DT asdenoted by LDU/T2--T1). When the time TIME is T2 ≦TIME <T3, the controlflow proceeds along Steps 53→55→56, at which the average up directiondemand PU(2) of the section II is corrected in the same manner as atStep 54. Further, if the time TIME is T3 ≦TIME <T4, the control flowproceeds along Steps 55→57→58, at which the average up direction demandPU(3) of the section III is corrected in the same manner as at Step 54.

In this way, the average up direction demands PU(1)-PU(3) of thesections I-III are sequentially corrected in the up demand calculatingprogram 14.

Next, the down demand calculating program 15 is actuated. This programsequentially corrects the average down direction demands PD(1)-PD(3) ofthe sections I-III likewise to the up demand calculating program 14, andwill not be further explained.

Next, the average demand estimating program 16 is actuated.

Only when the time TIME arrives at the boundary T4 which is the end timeof the section III, the following Steps 62-65 are executed. At Step 62,the counter J is initialized to 1 (one). At Step 63, the predictiveaverage up direction demand PUL(J) calculated till the preceding day ismultiplied by (1-SA) and is added to the average up direction demandPU(J) just measured on the particular day as multiplied by SA, to set apredictive average up direction demand PUL(J) anew. Likewise, thepredictive average down direction demand PDL(J) is set again. The valueof the counter J is decided at Step 64. Unless it reaches 3, 1 (one) isadded to the counter J at Step 65, whereupon the control flow returns toStep 63 so as to repeat the calculations of Step 63→Step 64→Step 65.When the demands have been calculated up to the section III, the valueof the counter J becomes 3, and the program proceeds from Step 64 to itsexit.

In this fashion, according to the average demand estimating program 16,the calculations are executed for correcting the predictive average updirection demands PUL(1)-PUL(3) and predictive average down directiondemands PDL(1)-PDL(3) in the respective sections I-III every day.

Next, the output program 17 is actuated. It delivers from the outputcircuit 3E the predictive average up direction demands PUL(1)-PUL(3) andpredictive average down direction demands PDL(1)-PDL(3) in therespective sections I-III calculated by the average demand program 16.

In the embodiment, the weight coefficient SA is set at a large value atthe beginning after the completion of a building, and it is set at asmaller value gradually with increase in the number of times ofcumulation CNT of the demand measurements. Therefore, the prediction ofthe demand quickly following up the change of the representative valueP_(k) of the demand is permitted at the beginning after the completionof the building. Moreover, the prediction of the demand which is notaffected by the random variation of daily data is permitted about thetime when the representative value P_(k) of the demand has becomestable.

In addition, when the number of times of cumulation CNT has exceeded theupper limit value, it is once reset to zero. Therefore, in a building inwhich the change of the representative value P_(k) of the demand arisesin a comparatively short period of time, a demand prediction having acomparatively good follow-up property is automatically effected inresponse to the change of the representative value P_(k). In a casewhere the change of the demand has been clearly found, the predictivevalue of the demand should desirably be urgently caused to follow it up.In such case, the weight coefficient SA can be corrected according tothe operator's judgement by operating the weight coefficient appointingswitch 2. It is therefore possible to promptly predict the demand at astill higher precision.

Further, in the embodiment, even when the weight coefficient SA has beenaltered to a large value (that is, when the representative value P_(k)of the demand has changed greatly), the new predictive value of thedemand is corrected sequentially from the predictive value obtained tillthen. When, in such case, the weight coefficient is set so as to become1 (one) only in the first demand prediction immediately after thealteration of the weight coefficient SA to the large value, themeasurement value P_(k) (l) of the first demand prediction mentionedabove becomes the predictive value P_(k) (l) as it is. It is thereforeto be understood that the follow-up property becomes still better.

Although, in the embodiment, three values have been set as the setvalues of the weight coefficient SA based on the number of times ofcumulation CNT or the switch data SWT, they are not restrictive thereto.Values in a number suited to the particular building may be chosen.

Further although the same weight coefficient SA has been used for therespective sections, different weight coefficients SA may well be setfor the respective sections. This realizes a demand prediction of highprecision for each section.

Furthermore, a demand prediction having a good follow-up property canalso be effected in such a way that, each time a demand is measured, ameasured result obtained till then is compared with a result measuredthis time, and when any sign of the change of the representative valueP_(k) of the demand has been detected as the result, the number of timesof cumulation CNT is reset to zero by way of example.

It is to be understood that the invention is also applicable to a caseof predicting demands in four or more sections or a case of predictingdemands for respective floors (in individual directions).

The invention is not restricted to the case of estimating the trafficvolume of elevators, but it is also applicable to cases of estimatingvarious demands such as electric power demand and water quantity demand.

As set forth above, according to this invention, among the measurementvalues of a demand in each section, a new one is weighted more than anold one, the new measurement value being then used, and once apredetermined condition such an an increase in the number of times ofcumulation of demand measurements has held, the degree of the weightingof the new measurement value is changed, so that both when therepresentative value of the demand has changed and when it is stable,the demand can be estimated at high precision.

There will now be described a practicable emodiment on how to use theswitch 2.

FIGS. 11 and 12 correspond to the RAM 3C and ROM 3D shown in FIGS. 4 and5, respectively. In a RAM 103C, the same data as in the RAM 3C exceptfor the data CNT in this RAM 3C is stored. In a ROM 103D, the same dataas in the ROM 3D except for the data N1 N2 NMAX and A(1)-A(3) in thisROM 3D is stored. In the ROM 103D, the values of data A(1)-A(4) arerespectively set at 0, 0.05, 0.1 and 0.2.

FIGS. 13 to 16 show the details of some of the programs in FIG. 6.Numeral 121 indicates the operating step of the initializing program 11,numerals 131 and 132 the operating steps of the weight coefficientsetting program 13, numerals 141-148 the operating steps of the updemand calculating program 14, and numerals 151-155 the operating stepsof the average demand estimating program 16.

The operations of the second embodiment will be explained below.

The number-of-persons detectors 6A-6C produce signals proportional tothe numbers of passengers on the cages 5A-5C, respectively. Thenumber-of-getting on persons calculations devices 7A-7C calculate thenumbers of persons who have gotton on the cages 5A-5C, respectively.These numbers of persons are classified into the numbers of persons inthe up direction and in the down direction by the change-over devices8A-8C, whereupon the numbers of persons in the respective directions areadded by the number-of-up pasengers addition device 9A and thenumber-of-down passengers addition device 9B. Thus, the number-of-uppassengers signal 9Aa and the number-of-down passengers signal 9Ba areprovided and sent to the input circuit 3A. In addition, the number ofcounts produced when the value "1" is counted every 5 minutes since atime 0 o'clock is provided as the timing signal 1a from the clock means1, and it is inputted to the input circuit 3A.

On the other hand, when the control device 3 is first connected to apower source, the initializing program 11 is actuated. Morespecifically, at Step 121, the initial values PU1-PU3 are respectivelyset for the predective average up direction demands PUL(1)-PUL(3), andthe intial values PD1-PD3 are respectively set for the predictiveaverage down direction demands PDL(1)-PDL(3). Subsequently, the controlflow shifts to the input program 12.

The input program 12 is a well-known program which feeds the inputsignal from the input circuit 3A into the RAM 3C. By way of example,when the time is 8 o'clock, the input program reads the value 96 fromthe input circuit 3A and sets the time TIME of the RAM 3C at 96.Likewise, the switch signal 2a is received and set as the switch dataSWT, the number-of-up passengers signal 9Aa is received and set as theup direction demand LDU, and the number-of-down passengers signal 9Ba isreceived and set as the down direction demand LDD.

Next, the weight coefficient setting program 13 is actuated. At Step131, it is decided whether or not the first time zone in which theaverage demand is to be calculated has been reached. When the time TIMEis equal to the boundary T1, the control flow proceeds to Step 132,whereat a constant value A(SWT) corresponding to the value of the switchdata SWT is set as the weight coefficient SA. For example, when it isclearly known that a demand whose magnitude differs from the ordinaryone will be measured on account of a national holiday, the beginning orend of the year, or the like, the operator sets the switch 2 at 1 (one).Since, at this time, the value of the switch data SWT also becomes 1(one), the constant value A(1) (=0) is set as the weight coefficient SA.On the other hand, when it is known that a demand whose magnitudediffers from the ordinary one will be measured though temporarily, onaccount of a conference, assembly or the like held in the building, theoperator sets the switch 2 at 2 or 3. At this time, the constant valueA(2) (=0.05) or constant value A(3) (=0.1) which is smaller than theconstant value A(4) (=0.2) in the ordinary operation of the elevators isset as the weight coefficient SA. In this manner, when it is previouslyknown that an unusual demand magnitude will be measured, the value ofthe weight coefficient SA is set at zero or the smaller value than theusual one in accordance with the extent or period to or during which themeasurement value will differ, whereby any bad influence on theestimation value of the demand can be prevented. When the time TIME isunequal to the boundary T1 at Step 131, the above step 132 is notexecuted, and the weight coefficient SA is not corrected.

In this way, according to the weight coefficient setting program 13,before the average demand is calculated every day, the weightcoefficient is corrected in accordance with the appointment through theswitch 2.

Next, the up demand calculating program 14 is actuated.

At Step 141, it is decided whether or not the time zone in which theaverage demand is to be calculated has been reached. When the time TIMEis smaller than the boundary T1, the control flow proceeds to Step 142,at which all the average up direction demands PU(1)-PU(3) are set atzero as the initializing operation for the calculation of the averagedemand. When the time TIME becomes equal to or greater than the boundaryT1 at Step 141, the control flow proceeds to Step 143. When the timeTIME is smaller than the boundary T2 here, the control flow proceeds toStep 144, at which the average up direction demand PU(1) of the sectionI is corrected by the use of the up direction demand LDU measured anew,so as to increase to the amount of the up direction demand per unit timeDT as denoted by LDU/(T2 -T1). When the time TIME is T2 ≦TIME <T3, thecontrol flow proceeds along Steps 143→145→146, at which the average updirection demand PU(2) of the section II is corrected in the same manneras at Step 144. Further, if the time TIME is T3 ≦TIME <T4, the controlflow proceeds along Steps 145→147→148, at which the average up directiondemand PU(3) of the section III is corrected in the same manner as atStep 144.

In this way, the average up direction demands PU(1)-PU(3) of thesections I-III are sequentially corrected in the up demand calculatingprogram 14.

Next, the down demand calculating program 15 is actuated. This programsequentially corrects the average down direction demands PD(1)-PD(3) ofthe sections I-III likewise to the up demand calculating program 14, andwill not be explained in detail.

Next, the average demand estimating program 16 is actuated.

Only when the time TIME arrives at the boundary T4 which is the end timeof the Section III, the following Steps 152-155 are executed. At Step152, the counter J is initialized to 1 (one). At Step 153, thepredictive average up direction demand PUL(J) calculated till thepreceding day is multiplied by (1-SA) and is added to the average updirection demand PU(J) just measured on the particular day as multipliedby SA, to set a predictive average up direction demand PUL(J) anew.Likewise, the predictive average down direction demand PDL(J) is setagain. The value of the counter J is decided at Step 154. Unless itreaches 3, 1 (one) is added to the counter J at Step 155, whereupon thecontrol flow returns to Step 153 so as to repeat the calculations ofStep 153→Step 154→Step 155. When the demands have been calculated up tothe section III, the value of the counter J becomes 3, and the programproceeds from Step 154 to its exit.

In this fashion, according to the average demand estimating program 16,the calculation are executed for correcting the predictive average updirection demands PUL(1)-PUL(3) and predictive average down directiondemands PDL(1)-PDL(3) in the respective sections I-III every day.

Next, the output program 17 is actuated. It delivers from the outputcircuit 3E the predictive average up direction demands PUL(1)-PUL(3) andpredictive average down direction demands PDL(1)-PDL(3) in therespective sections I-III calculated by the average demand program 16.

Although, in the embodiment, three values have been set as the setvalues of the weight coefficient SA, they are not respective thereto.Values in a number suited to the particular building may be set.

Further, although the same weight coefficient SA has been used for therespective sections, different weight coefficients SA may well be setfor the respective sections. This realizes a demand prediction of highprecision for each section.

Further, it is to be understood that the invention is also applicable toa case of predicting demands in four or more sections or a case ofpredicting demands for respective floors (in individual directions).

The invention is not restricted to the case of estimating the trafficvolume of elevators, but it is also applicable to cases of estimatingvarious demands such as electric power demand and water quantity demand.

As set forth above, according to the second embodiment, the estimationvalue of a demand is obtained in accordance with the measurement valueof the demand in each section, and the extent of use of the measurementvalue of the demand is selected in accordance with the appointment of aswitch, so that even when clearly a demand magnitude different from anordinary one will be measured, the demand magnitude during the ordinaryoperation can be precisely estimated without being affected by thedifferent demand magnitude.

What is claimed is:
 1. A demand estimation apparatus for controllingmachines wherein a cycle of a cyclically fluctuating demand is dividedinto a plurality of sections of given time widths comprising:means formeasuring the demand in each section by cumulating demand meaurementstaken a varying number of times for each section and producing measureddemand values with an increasing weighting parameter for successivelynewer measured values; means for determining an estimated value for thedemand in each section on the basis of the measured value of the demandin each section and a weight coefficient; and weighting setting means tochange the weight coefficient for the estimated demand values for agiven section in accordance with the number of times of cumulation ofdemand measurements for said given section varying from a preset lowerlimit value to a preset upper limit value; and when the number of timesof cumulation of the demand measurement for a given section has reachedthe preset upper limit value, the number of times of cumulation is resetto the preset lower limit whereupon the weight coefficient is changed.2. A demand estimation apparatus as defined in claim 1 wherein, as thenumber of times of cumulation of the demand measurements becomes largerfor a given section, the weight coefficient is made smaller.
 3. A demandestimation apparatus for controlling machines wherein a cycle of acylically fluctuating demand is divided into a plurality of sections ofgiven time widths comprising:means for measuring the demand in eachsection by cumulating demand measurements taken a varying number oftimes for each section and producing measured demand values with anincreasing weighting parameter for successively new measured values;means for determining an estimated value for the demand in each sectionon the basis of the measured value of the demand in each section and aweight coefficient; and weighting setting means to change the weightcoefficient for the estimated demand values for a given section inaccordance with the number of times of cumulation of demand measurementsfor said given section varying from a preset lower limit value to apreset upper limit value, said number of times of cumulation of demandmeasurements being reset to the preset lower limit value when the demandsubstantially changes.
 4. A demand estimation apparatus for controllingmachines wherein a cycle of a cyclically fluctuating demand is dividedinto a plurality of sections of given time widths comprising:means formeasuring the demand in each section by cumulating demand measurementstaken a varying number of times for each section and producing measureddemand values with an increasing weighting parameter for successivelynew measured values; means for determining an estimated value for thedemand in each section on the basis of the measured value of the demandin each section and a weight coefficient; and weighting setting means tochange the weight coefficient for the estimated demand values for agiven section in accordance with the number of times of cumulation ofdemand measurements for said given section varying from a preset lowerlimit value to a preset upper limit value and in accordance with aninput signal produced by a switch connected to said weighting settingmeans.
 5. A demand estimation apparatus as defined in claim 4, furthercomprising selection means connected to said switch for selecting theweight coefficient in accordance with a position of the switch.
 6. Ademand estimation apparatus as defined in claim 5 wherein, when underconditions different from predetermined conditions, the selection meansselects a weight coefficient smaller than a coefficient set by saidpredetermined conditions.
 7. A demand estimation apparatus as defined inclaim 5 wherein the section means stops selecting the weight coefficientwhen said coefficient has reached a predetermined value.